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Tracking of Walking Human Based on Position Uncertainty of Dynamic Vision Sensor of Quadcopter UAV
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 Title & Authors
Tracking of Walking Human Based on Position Uncertainty of Dynamic Vision Sensor of Quadcopter UAV
Lee, Junghyun; Jin, Taeseok;
 
 Abstract
The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.
 Keywords
quadcopter;vision;recognition;Kalman filter;estimation;
 Language
Korean
 Cited by
 References
1.
V. Sikiric, "Control of quadrocopter," Master of Science Thesis, p. 160, 2008.

2.
K. J. Atrom and T. Haglund, PID Controllers: Theory, Design, and Tuning, Instrument Society of America, 1995.

3.
D. P. Atherton and S. Majhi, "Limitations of PID controllers," Proc. of the American Control Conference, vol. 6, pp. 3843-3847, Jun. 1999.

4.
D. H. Yu, J. H. Park, J. H. Ryu, and K. T. Chong, "Attitude control of quad-rotor by improving the reliability of multi-sensor system," Transactions of the Korean Society of Mechanical Engineers A, vol. 39, no. 5, pp. 517-526, 2015.

5.
M. G. Yoo and S. K. Hong, "Target tracking control of a quadrotor UAV using vision sensor," Journal of the Korean Society for Aeronautical & Space Sciences, vol. 40, no. 2, pp. 118-128, 2012.

6.
E.-H. Ha, "Kalman filtering in position control using a vision sensor," Proc. of International Conference on Control Automation and Systems (ICCAS), pp. 1252-1254, 2010.

7.
V. Grabe, H. H. Bulthoff, and P. R. Giordano, "Onboard velocity estimation and closed-loop control of a quadrotor UAV based on optical flow," Proc. of IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2012.

8.
Y. K Kim, O. S. Kwon, Y. W Cho, and K. S. Seo, "Genetic programming based illumination robust and non-parametric multi-colors detection model," Korea Institute of Intelligent Systems, vol. 20, no. 6, pp. 780-785, 2010.

9.
F. Fahimi and K. Thakur, "An alternative closed-loop vision-based control approach for Unmanned Aircraft Systems with application to a quadrotor," IEEE International Conference on Unmanned Aircraft Systems (ICUAS), 2013.

10.
H. Deng, X. Zhao, and Z. G. How, "A vision-based ground target tracking system for a small-scale autonomous helicopter," Proc. of Fifth International Conference on. IEEE Image and Graphics (ICIG'09), 2009.

11.
S. Yang, S. A. Scherer, and A. Zell, "An onboard monocular vision system for autonomous takeoff, hovering and landing of a micro aerial vehicle," Journal of Intelligent & Robotic Systems, vol. 69, no. 4 pp. 499-515, 2013. crossref(new window)

12.
S. Bouabdallah, P. Murrieri, and R. Siegwart, "Design and control of an indoor micro quadrotor," Proc. of the 2004 IEEE International Conference on Robotics & Automation, pp. 4393-4398, 2004.

13.
J. H. Seung, D. J. Lee, J. H. Ryu, and K. T. Chong, "Precise positioning algorithm development for quadrotor flying robots using dual extended Kalman Filter," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 19, no. 2, pp. 158-163, 2013.

14.
R. Smith and P. Cheeseman, "On the representation of spatial uncertainty," The International Journal of Robotics Research, vol. 5, no. 4, pp. 56-68, 1986. crossref(new window)

15.
M. Fatan, B. L. Sefidgari, and A. V. Barenji, "An adaptive neuro PID for controlling the altitude of quadcopter robot," Proc. of 2013 18th International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 662-665, 2013.

16.
M. N. Duc, T. N. Trong, and Y. S. Xuan, "The quadrotor MAV system using PID control," Proc. of 2015 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 506-510, 2015.

17.
T. S. Jin, "Navigation trajectory control of security robots for restrict access potential falling accident areas for the elderly," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 21, no. 6, pp. 497-502, 2015.